Neural networks : tricks of the trade
It is our belief that researchers and practitioners acquire, through experience and word-of-mouth, techniques and heuristics that help them successfully apply neural networks to di cult real world problems. Often these \tricks" are theo- tically well motivated. Sometimes they are the result of...
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| Auteur principal: | |
|---|---|
| Autres auteurs: | |
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Collection: | Lecture notes in computer science
1524 |
| Sujets: | |
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Neural networks, tricks of the trade, Klaus-Robert Müller, Genevieve B. Orr, eds, 1998, New York, Springer, 1 vol. (VI-432 p.), Lecture notes in computer science, 3-540-65311-2 • Neural Networks: Tricks of the Trade, Texte imprimé, 9783662198131 |
Table des matières:
- Speeding Learning
- Efficient BackProp
- Regularization Techniques to Improve Generalization
- Early Stopping - But When?
- A Simple Trick for Estimating the Weight Decay Parameter
- Controlling the hyperparameter search in MacKay s Bayesian neural network framework
- Adaptive Regularization in Neural Network Modeling
- Large Ensemble Averaging
- Improving Network Models and Algorithmic Tricks
- Square Unit Augmented Radially Extended Multilayer Perceptrons
- A Dozen Tricks with Multitask Learning
- Solving the Ill-Conditioning in Neural Network Learning
- Centering Neural Network Gradient Factors
- Avoiding roundoff error in backpropagating derivatives
- Representing and Incorporating Prior Knowledge in Neural Network Training
- Transformation Invariance in Pattern Recognition Tangent Distance and Tangent Propagation
- Combining Neural Networks and Context-Driven Search for Online, Printed Handwriting Recognition in the Newton
- Neural Network Classification and Prior Class Probabilities
- Applying Divide and Conquer to Large Scale Pattern Recognition Tasks
- Tricks for Time Series
- Forecasting the Economy with Neural Nets: A Survey of Challenges and Solutions
- How to Train Neural Networks.